Lecture by Muhammad Usman – rescheduled
Due to unforeseen circumstances, today’s (15 December) lecture by Muhammad Usman has been cancelled. We apologize for any inconvenience this may cause. We will inform you of the new date for the lecture as soon as it is scheduled.
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Muhammad Usman, a PhD student in the Department of Data Science, specializes in spatial econometrics and machine learning techniques, with a focus on analyzing child health outcomes in regions vulnerable to climate change and conflict.
During the seminar, organized by the Spatial Warsaw Center, the speaker will discuss the topic: „Disentangling the heterogeneous effects of climate shocks and conflict exposure on child malnutrition”. [The abstract of the presentation is provided below.]
The lecture will take place on 15 December at 17:00 in room B111. Those interested in attending remotely are kindly asked to contact Dr Kateryna Zabarina at: wA12-3_akIF?G4CfZt}#hlE]#[c8moi$IPM`=*&A5^cZb{q].
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Child malnutrition remains a persistent public health challenge in low-and middle-income countries, driven by complex and spatially uneven environmental and socio-political stressors. This study examines the spatially heterogeneous effects of climate variability and conflict exposure on childhood malnutrition in Pakistan focusing primarily on stunting using high-resolution gridded data from 2001 to 2017. By integrating satellite-derived climate indicators, geolocated conflict events, and socioeconomic covariates, we employ a suite of spatially explicit modelling approaches including Geographically Weighted Regression (GWR), Multiscale GWR (MGWR), and Mixed GWR. Results indicate that the impacts of climatic shocks especially drought intensity and extreme precipitation are highly location-dependent and operate at different spatial scales. Conflict exposure further intensifies these adverse effects in vulnerable and socioeconomically deprived regions, with MGWR revealing stronger fine-scale variations compared to traditional GWR. Mixed GWR identifies a combination of global drivers (e.g., long-term socioeconomic deprivation) and locally varying predictors (e.g., seasonal drought anomalies and conflict proximity). Collectively, the findings highlight substantial spatial heterogeneity in the determinants of child malnutrition and demonstrate that ignoring local variations can mask critical pockets of vulnerability. This study provides a nuanced understanding of how climate and conflict interact across space to influence child health outcomes. The results underscore the need for spatially tailored and multisectoral policy interventions that address both environmental and political fragility to effectively reduce child malnutrition.